Can I create new tasks directly through my agent?

Yes. Use the `create_action` tool to generate new tasks in a specific workspace. You provide the title and workspace ID, and your agent will handle the backend orchestration to create the action instantly.

How do I find my Workspace ID?

Ask your agent to `list_workspaces`. It will return a list of all workspaces you have access to, along with their unique IDs, which are required for project and action operations.

Can I see the templates we have defined for repeatable workflows?

Absolutely. Use the `list_templates` tool to see all action templates in a workspace. This helps your agent understand the predefined workflows your team uses for consistent project delivery.

Hive (Project Management) MCP Server for CrewAI 7 tools — connect in under 2 minutes

Name: Hive (Project Management)
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 7 Tools Framework

Connect your CrewAI agents to Hive (Project Management) through the Vinkius — pass the Edge URL in the `mcps` parameter and every Hive (Project Management) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Hive (Project Management) Specialist",
    goal="Help users interact with Hive (Project Management) effectively",
    backstory=(
        "You are an expert at leveraging Hive (Project Management) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Hive (Project Management) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Hive (Project Management) MCP Server

Connect your Hive account to any AI agent and take full control of your project management and team collaboration through natural conversation.

When paired with CrewAI, Hive (Project Management) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Hive (Project Management) tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Workspace Management — List all available workspaces and navigate across different tenant environments effortlessly
Project Tracking — Analyze grouping schemas linking large initiatives and monitor the status of team projects directly from your agent
Action Items — Create and list operational tasks (actions), linking precise items and checking team assignments in real-time
Detailed Inspection — Retrieve exact metadata and structural details for specific action IDs to understand progress and blockers
Taxonomy & Labels — Discover discrete visual categorizations and taxonomy matrices used to organize your workspace items
Workflow Templates — Enumerate active repeatable workflows and action templates to maintain process consistency across your team

The Hive (Project Management) MCP Server exposes 7 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Hive (Project Management) to CrewAI via MCP

Follow these steps to integrate the Hive (Project Management) MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 7 tools from Hive (Project Management)

Why Use CrewAI with the Hive (Project Management) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Hive (Project Management) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Hive (Project Management) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Hive (Project Management) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Hive (Project Management) for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Hive (Project Management), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Hive (Project Management) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Hive (Project Management) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Hive (Project Management) MCP Tools for CrewAI (7)

These 7 tools become available when you connect Hive (Project Management) to CrewAI via MCP:

create_action

Create action

get_action

Get action

list_actions

List actions

list_labels

List labels

list_projects

List projects

list_templates

List action templates

list_workspaces

List workspaces

Example Prompts for Hive (Project Management) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Hive (Project Management) immediately.

"List all projects in my 'Marketing' workspace (ID: ws-marketing)"

"Create a new action called 'Finalize Budget' in workspace 'ws-finance'"

"What are the action templates available in the 'Engineering' workspace?"

Troubleshooting Hive (Project Management) MCP Server with CrewAI

Common issues when connecting Hive (Project Management) to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Hive (Project Management) + CrewAI FAQ

Common questions about integrating Hive (Project Management) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.